filename approachability arousal danceability
Length:90 Min. :-0.04635 Min. :3.113 Min. :0.04688
Class :character 1st Qu.: 0.32716 1st Qu.:4.221 1st Qu.:0.24611
Mode :character Median : 0.49057 Median :4.876 Median :0.57643
Mean : 0.48547 Mean :4.845 Mean :0.55829
3rd Qu.: 0.65034 3rd Qu.:5.476 3rd Qu.:0.88237
Max. : 0.95809 Max. :7.022 Max. :1.00000
engagingness instrumentalness tempo valence
Min. :0.1041 Min. :0.1310 Min. : 30.00 Min. :3.429
1st Qu.:0.5238 1st Qu.:0.4775 1st Qu.: 84.00 1st Qu.:4.671
Median :0.6452 Median :0.6166 Median : 97.50 Median :5.191
Mean :0.6750 Mean :0.6091 Mean : 99.61 Mean :5.092
3rd Qu.:0.8807 3rd Qu.:0.7762 3rd Qu.:117.00 3rd Qu.:5.480
Max. :1.0301 Max. :0.9554 Max. :176.00 Max. :6.402
My two songs are “make your transition” by Omaks, and “Rampage (VIP Mix)” by Bollman. I acquired them via soundcloud, as they were labeled as free downloads. These two songs are among my favourite to dance to on a rave/festival, or even in my own time. The reason I chose to download existing songs from soundcloud is because I think these DJ’s make enough money already. Another reason is that when I tried creating songs with AI, no good techno came from it, which is what I wanted.
My first visualization, for now only the ‘bad’ plot with the compmus dataset
Here the arousal is plotted against the tempo. Not much is visible in this plot.
Here I will conclude my research on the chosen music, for now